Abstract
The introduction of proportional-integral-derivative (PID) controllers into cooperative collision avoidance systems (CCASs) has been hindered by difficulties in their optimization and by a lack of study of their effects on vehicle driving stability, comfort, and fuel economy. In this paper, we propose a method to optimize PID controllers using an improved particle swarm optimization (PSO) algorithm, and to better manipulate cooperative collision avoidance with other vehicles. First, we use PRESCAN and MATLAB/Simulink to conduct a united simulation, which constructs a CCAS composed of a PID controller, maneuver strategy judging modules, and a path planning module. Then we apply the improved PSO algorithm to optimize the PID controller based on the dynamic vehicle data obtained. Finally, we perform a simulation test of performance before and after the optimization of the PID controller, in which vehicles equipped with a CCAS undertake deceleration driving and steering under the two states of low speed (≤50 km/h) and high speed (≥100 km/h) cruising. The results show that the PID controller optimized using the proposed method can achieve not only the basic functions of a CCAS, but also improvements in vehicle dynamic stability, riding comfort, and fuel economy.
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Project supported by the National Natural Science Foundation of China (No. 61300145)
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Wu, Xc., Qin, Gh., Sun, Mh. et al. Using improved particle swarm optimization to tune PID controllers in cooperative collision avoidance systems. Frontiers Inf Technol Electronic Eng 18, 1385–1395 (2017). https://doi.org/10.1631/FITEE.1601427
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DOI: https://doi.org/10.1631/FITEE.1601427
Key words
- Cooperative collision avoidance system (CCAS)
- Improved particle swarm optimization (PSO)
- PID controller
- Vehicle comfort
- Fuel economy